Evaluating Spatial Skyline Queries on Changing Data
The amount of data being handled is enormous these days. To identify relevant data in large datasets, Skyline queries have been proposed. A traditional Skyline query selects those points that are the best ones based on user’s preferences. Spatial Skyline Queries (SSQ) extend Skyline queries and allow the user to express preferences on the closeness between a set of data points and a set of query points. However, existing algorithms must be adapted to evaluate SSQ on changing data; changing data are data which regularly change over a period of time. In this work, we propose and empirically study three algorithms that use different techniques to evaluate SSQ on changing data.
KeywordsSkyline queries Spatial Skyline queries changing data
Unable to display preview. Download preview PDF.
- 1.Borzsonyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: IEEE Conf. on Data Engineering, pp. 421–430 (2001)Google Scholar
- 5.Sharifzadeh, M., Shahabi, C.: The spatial skyline queries. In: VLDB 2006: Proceedings of the 32nd International Conference on Very Large Data Bases, pp. 751–762. VLDB Endowment (2006)Google Scholar
- 6.Sharifzadeh, M., Shahabi, C., Kazemi, L.: Processing spatial skyline queries in both vector spaces and spatial network databases, vol. 34, pp. 14:1–14:45. ACM, New York (2009)Google Scholar
- 7.Shen, H., Chen, Z., Deng, X.: Location-based skyline queries in wireless sensor networks. In: NSWCTC 2009: Proceedings of the 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing, pp. 391–395. IEEE Computer Society, Washington, DC (2009)CrossRefGoogle Scholar
- 8.Zheng, B., Lee, K.C.K., Lee, W.-C.: Location-dependent skyline query. In: 9th International Conference on Mobile Data Management, MDM 2008, pp. 148–155 (April 2008)Google Scholar